|The large amount of snow throughout the midwest each year is a familiar burden to many residents of Minnesota. The current methods of snow removal, namely using a shovel or a snow blower, still have a significant amount of human labor involved. The unique nature of the snow removal adds complexity to the automation of the process, in which obstacles must be navigated around and certain boundaries must not be crossed, all while moving the snow to a more acceptable location. To this end, the ION Autonomous Snowplow competition (ASC), a annual event held in St. Paul, Minnesota, challenges teams to competitively prove the validity of their plans for navigation and localization, along with their robot’s physical capability to complete the aforementioned tasks. GOFIRST Robotics at the University of Minnesota-Twin Cities placed first at the 8th annual ION ASC, with the teams focus on completing this process in a safe and efficient manner. Snow Squirrel, our autonomous snowplow, is a battery powered robot that uses LIDAR for localization and waypoint based navigation, and a camera for moving obstacle detection. In this presentation we will focus on the LIDAR only SLAM system used to map and position ourselves onto an unknown environment, using landmarks placed around the field. Lastly, we will also discuss the safety considerations made in the mechanical and electrical design, as well as the propulsion system employed on the robot.
Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018)
September 24 - 28, 2018
Hyatt Regency Miami
|1622 - 1638
|Cite this article:
Stiehm, Matt, Stroming, Austin, Eisenschenk, Brad, McCarthy, Clay, Sjostrand, Ryan, "Localization, Mapping, and Navigation using only a single 2D LiDaR," Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018), Miami, Florida, September 2018, pp. 1622-1638.
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